Data visualization and rapid analytics of seasonal climate and rice production data of Cotabato: Applying power BI to support agricultural decision making - Delena, Reymark D. (Animo Repository, 2023)
Rice cultivation is critical for food security, especially in nations where it is a staple crop, such as the Philippines. Droughts and La Nina occurrences have reduced rice output in Cotabato, resulting in food insecurity and even warfare. This study was undertaken to produce analytics with visualization utilizing seasonal climatic data and historical rice production data to understand the present situation of rice production. The study's goals were to identify and comprehend the data to be utilized in analytics, to investigate data mining methodologies, and to build and assess the usability of the analytical dashboard. A scoping study was done to collect relevant literature on the granularity of data, processes, and techniques utilized for analysis, and data visualization. Only 17 of the 66 publications were suitable, and they used data from diverse sources such as crop area, rainfall, soil moisture, radiation, humidity, and temperature. The Office of Provincial Agriculturist in Cotabato provided data on rice production in Cotabato from 2007 to 2021, including annual, irrigated, and rainfed rice production, as well as cropping area. Rainfall, soil moisture, radiation, humidity, and temperature data from 2007 to 2021 were obtained from the NASA POWER online dataset. The information was taken, converted, and imported into POWER BI for further examination. Based on the selected literature, spatial analysis, timeline analysis, and multivariate regression analysis were used to establish the relativeness of the given agro-climate dataset to rice production. Several methodologies were employed in the design and development of the analytical dashboard, including system architecture, use case diagram, entity-relationship diagram, and benchmark tasks. The agro-climate and rice production of Cotabato were visualized using Power BI, and numerous visualizations were developed from the exploratory analysis. Usability testing was used to evaluate the prototype using the benchmark and checklist of usability guidelines for evaluating information visualization systems. The prototype was found to be effective in displaying data in a clear and simple way, allowing users to immediately comprehend the information offered. Users said the prototype was efficient since it allowed them to do jobs fast and simply without any uncertainty. During the testing, however, certain flaws were discovered. The intricacy of several of the visuals made it difficult for users to grasp the information offered, making the prototype less learnable. Users also expressed dissatisfaction with the prototype, describing it as dull and uninteresting, and stating that the absence of interaction made it impossible for them to examine and change the data in a meaningful way. The design team improved the prototype based on the findings of usability testing, such as simplifying some of the visualizations, introducing additional interactive elements, and making the system more user-friendly. Iterative upgrades aided in the development of a more effective and user-friendly information system. visualization system. The proposed analytical dashboard emphasizes the significance of leveraging analytics and visualization to gain insights into the current state of rice production and the factors impacting it. The prototype developed as part of this study can assist stakeholders and policymakers in making informed decisions to address the issues of food insufficiency and conflict in Cotabato resulting from the decline in rice production. Keywords: rice production, data mining, data visualization, scoping review, agro-climate factors, irrigated and rainfed rice production, analytical dashboard, usability testing, climate change.